Description Usage Arguments Value Examples
View source: R/Deconvolve_transcriptome.R
Deconvolve_transcriptome
measures the similarity
of one or many query RNA-seq or microarray samples to samples
with known differentiation stage contained in the training models.
1 2 3 4 5 6 7 | Deconvolve_transcriptome(
transcriptome_data,
deconvolution_algorithm,
models,
nr_permutations,
output_file
)
|
transcriptome_data |
A data frame that contains the gene expression data. Rows are expected to be HGNC symbols and columns are expected to contain the samples. |
deconvolution_algorithm |
Which deconvolution algorithm to choose from. Options: 'music','bseqsc' (CIBERSORT), 'nmf'. |
models |
List of models to be used. Use show_models_NMF(), show_models_music() or show_models_bseqsc() to view available models or add new model via add_deconvolution_training_model_*(). |
nr_permutations |
Utilized to calculate p-value Higher amount of permutations generally lead to more precise p-value estimates. Default value 1000. |
output_file |
Path of output file. If not specified, no hard-disk written output will occur. |
Similarity measurements of differentiation stages.
1 2 3 4 | data("visualization_data")
Deconvolve_transcriptome(
transcriptome_data = visualization_data
)
|
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